GO Gradient for Expectation-Based Objectives

17 January 2019

Lawrence Carin

Papers citing "GO Gradient for Expectation-Based Objectives"

33 / 33 papers shown

Title
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 467 10,591 0 17 Feb 2020
ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks Mingzhang Yin Mingyuan Zhou MQ 118 11 0 30 Jul 2018
Pathwise Derivatives Beyond the Reparameterization Trick M. Jankowiak F. Obermeyer 145 113 0 05 Jun 2018
Implicit Reparameterization Gradients Michael Figurnov S. Mohamed A. Mnih BDL 105 234 0 22 May 2018
WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling Hao Zhang Bo Chen D. Guo Mingyuan Zhou BDL 73 118 0 04 Mar 2018
Backpropagation through the Void: Optimizing control variates for black-box gradient estimation Will Grathwohl Dami Choi Yuhuai Wu Geoffrey Roeder David Duvenaud 99 300 0 31 Oct 2017
Triangle Generative Adversarial Networks Zhe Gan Liqun Chen Weiyao Wang Yunchen Pu Yizhe Zhang Hao Liu Chunyuan Li Lawrence Carin GAN OOD 59 137 0 19 Sep 2017
ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching Chunyuan Li Hao Liu Changyou Chen Yunchen Pu Liqun Chen Ricardo Henao Lawrence Carin GAN FedML 65 223 0 05 Sep 2017
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC Yulai Cong Bo Chen Hongwei Liu Mingyuan Zhou BDL 61 66 0 06 Jun 2017
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference Geoffrey Roeder Yuhuai Wu David Duvenaud BDL 118 202 0 27 Mar 2017
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models George Tucker A. Mnih Chris J. Maddison John Lawson Jascha Narain Sohl-Dickstein BDL 226 282 0 21 Mar 2017
Wasserstein GAN Martín Arjovsky Soumith Chintala Léon Bottou GAN 172 4,827 0 26 Jan 2017
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 344 5,372 0 03 Nov 2016
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables Chris J. Maddison A. Mnih Yee Whye Teh BDL 196 2,538 0 02 Nov 2016
Operator Variational Inference Rajesh Ranganath Jaan Altosaar Dustin Tran David M. Blei 59 116 0 27 Oct 2016
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms C. A. Naesseth Francisco J. R. Ruiz Scott W. Linderman David M. Blei BDL 135 107 0 18 Oct 2016
The Generalized Reparameterization Gradient Francisco J. R. Ruiz Michalis K. Titsias David M. Blei BDL 83 169 0 07 Oct 2016
Energy-based Generative Adversarial Network Jiaqi Zhao Michaël Mathieu Yann LeCun GAN 139 1,114 0 11 Sep 2016
Improved Techniques for Training GANs Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen GAN 486 9,062 0 10 Jun 2016
Variational inference for Monte Carlo objectives A. Mnih Danilo Jimenez Rezende DRL BDL 161 290 0 22 Feb 2016
Rényi Divergence Variational Inference Yingzhen Li Richard Turner BDL 97 263 0 06 Feb 2016
Gamma Belief Networks Mingyuan Zhou Yulai Cong Bo Chen BDL 81 87 0 09 Dec 2015
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford Luke Metz Soumith Chintala GAN OOD 266 14,018 0 19 Nov 2015
MuProp: Unbiased Backpropagation for Stochastic Neural Networks S. Gu Sergey Levine Ilya Sutskever A. Mnih BDL 49 143 0 16 Nov 2015
Hierarchical Variational Models Rajesh Ranganath Dustin Tran David M. Blei DRL VLM 88 338 0 07 Nov 2015
The Poisson Gamma Belief Network Mingyuan Zhou Yulai Cong Bo Chen BDL 47 53 0 06 Nov 2015
Fast Second-Order Stochastic Backpropagation for Variational Inference Kai Fan Ziteng Wang J. Beck James T. Kwok Katherine A. Heller ODL BDL DRL 57 46 0 09 Sep 2015
Gradient Estimation Using Stochastic Computation Graphs John Schulman N. Heess T. Weber Pieter Abbeel OffRL 146 395 0 17 Jun 2015
Local Expectation Gradients for Doubly Stochastic Variational Inference Michalis K. Titsias BDL 43 9 0 04 Mar 2015
Deep Exponential Families Rajesh Ranganath Linpeng Tang Laurent Charlin David M. Blei BDL 45 153 0 10 Nov 2014
Neural Variational Inference and Learning in Belief Networks A. Mnih Karol Gregor BDL 184 729 0 31 Jan 2014
Black Box Variational Inference Rajesh Ranganath S. Gerrish David M. Blei DRL BDL 144 1,168 0 31 Dec 2013
Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression Tim Salimans David A. Knowles 118 252 0 28 Jun 2012